In the ongoing quest to better align products/services and the needs of customers, companies are increasingly developing competencies in data acquisition and analytics. Large volumes of data are gathered and analyzed for the purpose of gaining business intelligence and customer insights that allow companies to better understand the interaction between their products and the customer. These insights are also leveraged by companies to engage with their customers in a more meaningful and relevant fashion throughout the customer engagement cycle—from lead generation to the sales process, and on through the service and support phase into renewal and upsell activities.
Until recently, most of the data feeding the analytics and business intelligence machines has originated from within the organization, and thus is largely static and offline. It is generated by internal systems and employees, and is housed in large enterprise databases such as ERP and CRM systems, where it can be accessed by various groups within the organization. However, the recent run-up in popularity of social media platforms has resulted in the advent of a completely new and external source of customer data—the Internet and its myriad of sharing and networking sites. The development of sophisticated Internet search capabilities, and web hooks into various social networking platforms and web services has led many to realize that a considerable volume of customer data is available about consumers on the public World Wide Web, but organizing, filtering, and displaying that data to provide real insight and relevancy is a significant challenge.
It is an object of the present invention to obviate or mitigate some of the above disadvantages.